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Applicability of Hadamard relaxation method to MMW and THz Imaging with compressive sensing

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Abstract

Compressive sensing (CS) is widely considered a promising method for millimeter wave (MMW) and terahertz (THz) imaging, especially in security screening. In many real-life application scenarios, a CS reconstruction algorithm has to be simultaneously robust, noise-tolerant and fast to be of practical use. However, a lot of CS reconstruction algorithms are not designed aiming at such overall performance, preventing them to become applicable in commercial imaging systems. Having investigated some CS algorithms, we find that Hadamard relaxation method is a potential candidate for commercial CS imaging. By using MATLAB, we study Hadamard relaxation method focusing on its under-sampling ratio, tolerance to noise and efficiency. Comparisons with several other CS algorithms are made using the available data in references. The results demonstrate that the overall performance of Hadamard relaxation method is among the best for real-life and real-time applications of MMW and THz imaging.

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Acknowledgments

The authors thank Xiaoguang Tian, Pengsheng Wu, Kai Wang, Changlei Wang, Ting Li, Huakun Zhang and Tongshan Yuan for useful discussions on the algorithm and its applicability in real-life imaging systems. We give our sincere appreciations for the hard work of the reviewers and editors.

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Authors and Affiliations

  1. East China Research Institute of Electronic Engineering, Hefei, Anhui, China

    Hao Tu, Weihua Bu, Wenjing Wang, Bingxi Gao, Hui Feng & Shuai Wu

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  1. Hao Tu
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  2. Weihua Bu
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  3. Wenjing Wang
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Correspondence to Hao Tu.

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Tu, H., Bu, W., Wang, W. et al. Applicability of Hadamard relaxation method to MMW and THz Imaging with compressive sensing. SIViP 11, 399–406 (2017). https://doi.org/10.1007/s11760-016-0974-6

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  • DOI: https://doi.org/10.1007/s11760-016-0974-6

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